Utility of Nuclear Morphometry in Effusion Cytology

Abstract

Background: The cytological analysis of serous effusions is a common investigation and yields important diagnostic information. However, the distinction of reactive mesothelial cells from malignant cells can sometimes be difficult for the cytopathologist. Hence cost-effective ancillary methods are essential to enhance the accuracy of cytological diagnosis. The aim of this study was to examine the utility of nuclear morphometry in differentiating reactive mesothelial cells from malignant cells in effusion smears. Materials and Methods: Sixty effusion smears consisting of 30 effusions cytologically classified as malignant (adenocarcinomas) and 30 benign effusions showing reactive mesothelial cells were included in the study. ImageJ was used to measure the nuclear area, perimeter, maximal feret diameter, minimal feret diameter and the circularity. A total of ten representative cells were studied in each case. Results: Significant differences were found between benign and malignant effusions for the nuclear area, perimeter, maximal feret diameter and minimal feret diameter. No significant difference was found for circularity, a shape descriptor. Receiver operating characteristic (ROC) curve analysis revealed that nuclear area, perimeter, maximal feret diameter, and minimal feret diameter are helpful in discriminating benign and malignant effusions. Conclusions: Computerised nuclear morphometry is a helpful ancillary technique to distinguish benign and malignant effusions. ImageJ is an excellent cost effective tool with potential diagnostic utility in effusion cytology.

Nuclear Morphometry and Chromatin Texture Changes in Hepatocellular Carcinoma Samples May Predict Liver Transplant Patients’ Outcomes

“…Values de ned by the ROC curve related to AR are results not used in other studies. Sensitivity and speci city values for nuclear perimeter in our study are similar to the values found by Ambroise et al [23] who showed that a cut-off level of 33.2 µm for nuclear perimeter could differentiate malignant and benign pleural effusions. However, despite the computer analysis by ImageJ following a similar methodology, they used analyses applied to effusion cytology, in addition to evaluating for each case only ten representative nuclei from ten different elds.…”

\theta(1) time parallel algorithm for determining the diameters of multi-level image on the reconfigurable mesh computer machine

“…The procedure of finding the extreme PEs belonging to the sides of the quadrilateral is executed in 8 successive sub steps, that allow to identify the PEs ∈ {E, F, G, H, I, J, K, L} of the contour component. In each sub step, we applied the Min/Max algorithm [18] to the values of the abscissa and ordinates relating to the quadrilateral. The set of PEs belonging to this sub group are determined as follow: 1.…”

“…3. All the PE j of group G execute the algorithm Max [18] to identify the two PEs which has the maximum distance and represent the extreme points of the object, where Dmax = Max {d1, d2, d3, d4, d5, d6, d7, d8, d9, d10, d11, d12, d13, d14, d15, d16}). The two PEs {PE n , PE m } of the group G, refer to the two points that defines the maximum diameter, thus represent the two extreme points of the component.…”

“…While the other PEs of the group G go into the mode SB 4. PE n and PE m execute the Min (or Max) algorithm [18] to identify the one with the minimum or maximum ID. The PE with the minimum ID for example, transmits the two coordinates ( , ) and ( , ) to all the other PEs of the contour.…”

“…The diameter of objects in an image represents today an indispensable tool for the characterization and classification of forms. It is used as a measurement tool in a multitude of disciplines such as medical imagery [13], agriculture [1] [8], geology [7] [9] [15], nanotechnology [14], Composite Materials, Microstructures [10] [5], Microbiology and Medicine Biology [2] [18]. Most of the algorithms used in these fields are essentially based on determining the diameter of the smallest convex polygon that surrounds the component.…”